Article
Computer Science, Artificial Intelligence
Divya Bairathi, Dinesh Gopalani
Summary: The proposed improved salp swarm algorithm, by integrating multiple elements, enhances exploration and exploitation capabilities, making it more effective in solving complex multimodal problems.
Article
Engineering, Biomedical
Seyed Morteza Ghazali, Mousa Alizadeh, Jalil Mazloum, Yasser Baleghi
Summary: This study proposes a machine learning-based method that utilizes EEG signals to accurately diagnose epilepsy and related seizures by analyzing and extracting features from the signals.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Automation & Control Systems
Sandeep Rangi, Sheilza Jain, Yogendra Arya
Summary: In the rapidly evolving interconnected electric power system network, automatic generation control (AGC) plays a critical role in maintaining power supply quality and system security. A robust and smart AGC strategy is essential for better power quality. Cascade control schemes, specifically the COC-PIDN approach, show better performance in handling nonlinearity and continuous load changing. The COC-PIDN controller with a nature-inspired salp swarm algorithm for adjusting parameters demonstrates its effectiveness and robustness in two-area restructured reheat thermal systems and restructured two-area thermal-hydro systems, especially when combined with a redox flow battery.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Environmental Sciences
Francis Otieno, Sanjay Kumar Shukla
Summary: This paper reviews the failure modes, mechanisms, and possible solutions to enhance the stability and safety of iron ore tailings dams through a comprehensive investigation of 16 failure cases. The analysis shows that most failures were caused by slope instability, overtopping, liquefaction-related instability, foundation failure, erosion, and structural failure. 25% of the failure cases had unknown causes. Prevention and remediation measures are also presented to avoid future failures and associated negative environmental impacts.
INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT
(2023)
Article
Computer Science, Artificial Intelligence
Mohammed Azmi Al-Betar, Sofian Kassaymeh, Sharif Naser Makhadmeh, Salam Fraihat, Salwani Abdullah
Summary: This research proposes the use of FFNN neural networks to develop an accurate cost forecasting model. The parameters of the predictor are optimized using an augmented version of the SSA algorithm, with the addition of search enhancement and elitism techniques. Experimental results demonstrate the superiority of the proposed techniques and their robustness, as supported by statistical validation.
APPLIED SOFT COMPUTING
(2023)
Article
Nuclear Science & Technology
Morteza Imani, Mahdi Aghaie
Summary: 180W is the lightest isotope of Tungsten with small abundance ratio, which can be separated by non-conventional single withdrawal cascades. This study develops a single withdrawal cascade model to evaluate multicomponent separation and investigates the parameters affecting the separation and equilibrium time. The results show that increasing the number of stages and the feed flow rate can improve the separation efficiency and decrease the cascade equilibrium time.
NUCLEAR ENGINEERING AND TECHNOLOGY
(2023)
Article
Environmental Sciences
Carlos Boente, Adrian Zafra-Perez, Juan Carlos Fernandez-Caliani, Ana Sanchez de la Campa, Daniel Sanchez-Rodas, Jesus D. de la Rosa
Summary: Mining activities release large amounts of particulate matter into the atmosphere, which can have harmful effects on human health and ecosystems. This study assessed the impact of a polymetallic mine in Southwest Spain on nearby populations. PM10 sampling was conducted in three villages over a year, and high PM10 concentrations were found near the mine during spring and summer. High enrichments of As, Cu, Pb, and Zn were observed in all locations. However, the risk assessment showed that carcinogens were within permissible limits even in the closest village.
ATMOSPHERIC ENVIRONMENT
(2023)
Article
Environmental Studies
Hongquan Guo, Hoang Nguyen, Diep-Anh Vu, Xuan-Nam Bui
Summary: This study developed and compared four AI techniques for estimating mining capital cost in open-pit copper mining projects, finding that the artificial neural network (ANN) model had the highest accuracy due to factors such as production capacity.
Article
Mathematics
Enrique Jelvez, Julian Ortiz, Nelson Morales Varela, Hooman Askari-Nasab, Gonzalo Nelis
Summary: This paper proposes a methodology that incorporates geological uncertainty at all stages of open pit mining operations, using new mathematical optimization models and conditional simulation. The method is tested in a real case study to evaluate its impact on solution quality and to guide decision-making by assessing the relative importance of uncertainty at each stage.
Article
Engineering, Environmental
Feifei Wang, Qingyang Ren, Xueliang Jiang, Anmin Jiang, Congcong Zhao, Weijun Liu
Summary: The subsidence mechanism of the mountain surface in the Daliang Lead-zinc Ore Mine in China was studied through field investigations and numerical simulations. The results revealed the dominant structural planes of the dolomite and ore body, and reproduced the formation process of landslide through numerical modeling. The research findings provide important references for mine safety production and collapse pit treatment.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2022)
Article
Engineering, Chemical
Oscar A. Marin, Andrzej Kraslawski, Luis A. Cisternas
Summary: The mining industry generates a large amount of waste, some harmful to the environment while others valuable. Reprocessing mine tailings is becoming increasingly important, requiring the development of a simple method for assessing profitability. The study proposes a method for estimating the cost of mine tailings processing, applicable for other countries.
MINERALS ENGINEERING
(2022)
Article
Environmental Studies
Sena Senses, Mustafa Kumral
Summary: This paper presents a comprehensive analysis of earthquakes in a mining area and evaluates their impacts on a mining operation through a case study based on a mine construction project. The study highlights the importance of considering extreme natural events, such as earthquakes, in mining project planning and risk mitigation, providing valuable insights for project management practices.
Article
Environmental Sciences
Guang Li, Shuai-qi Liu, Feng-shan Ma, Jie Guo, Xin Hui
Summary: Long-term field monitoring has revealed that serious surface subsidence can occur despite the use of high strength cemented fill method. By combining numerical simulations and GPS monitoring, the ground subsidence mechanism of a typical filling mining mine with a steeply inclined ore body was analyzed. The results show that the subsidence caused by mining steep ore bodies is characterized by two settlement centers and uneven spatial distribution. The backfill does improve strength and reduces settlement amplitude, but it cannot prevent subsidence under continuous and repeated mining disturbances.
JOURNAL OF MOUNTAIN SCIENCE
(2023)
Article
Environmental Sciences
Michelle Mimi Vandyck, Emmanuel Kwesi Arthur, Emmanuel Gikunoo, Frank Ofori Agyemang, Bennetta Koomson, Gordon Foli, Douglas Siaw Baah
Summary: Remedial action is necessary to prevent heavy metal leachability and environmental risks in contaminated soils. This study assessed the effectiveness of limekiln dust (LKD) as a stabilizing agent for Ghanaian gold mine tailings contaminated with heavy metals. The contaminated soils were amended with different doses of LKD, and various tests were conducted to evaluate their effectiveness. The results showed that 20 wt.% of LKD was effective in remediating the mine tailings, except for cadmium, and 10 wt.% of LKD was sufficient for Cd-contaminated soil remediation. The use of LKD to remediate soils contaminated with Fe, Cu, Ni, Cd, and Hg was found to be safe and environmentally friendly.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Computer Science, Information Systems
Xunhong Wang, Yonglin Tan, Lan Yang
Summary: This research considered both the technical indicators and the spatial distribution of ore grade in optimizing metal mine production, and applied an adaptive differential evolution algorithm for optimization. Experimental results showed that compared to other algorithms, this model had better convergence rate and global search ability in optimizing the technical indicators of metal mine production.
Article
Computer Science, Interdisciplinary Applications
Jue Zhao, Hoang Nguyen, Trung Nguyen-Thoi, Panagiotis G. Asteris, Jian Zhou
Summary: The study aimed to develop a novel computer-aided method for predicting the deflection of reinforced concrete beams under concentrated loads. The WOA-LMBPNN model was optimized to achieve higher accuracy in predicting DRCB, using 120 experiments as input parameters. Comparison between WOA-LMBPNN and PSO-LMBPNN models showed the effectiveness of WOA and the efficiency of the hybrid model in predicting DRCB.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Interdisciplinary Applications
Hoang Nguyen, Xuan-Nam Bui, Quang-Hieu Tran, Hoa Anh Nguyen, Dinh-An Nguyen, Le Thi Thu Hoa, Qui-Thao Le
Summary: This paper introduces a novel hybrid model combining MARS, PSO, and MLP algorithms to enhance the prediction of peak particle velocity in mine blasting. The proposed MARS-PSO-MLP model outperformed stand-alone models and achieved the highest accuracy and reliability.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Industrial
Weixun Yong, Wengang Zhang, Hoang Nguyen, Xuan-Nam Bui, Yosoon Choi, Trung Nguyen-Thoi, Jian Zhou, Trung Tin Tran
Summary: The construction of metropolises in smart cities is a trend in developed countries, but it may cause damages to the surrounding structures. To ensure the safety of the surrounding structures, diaphragm walls have been applied to prevent deformation or collapse. This study proposes two intelligent models based on the finite element method and metaheuristic algorithms to predict the deflection of diaphragm walls induced by deep braced excavations. The results show that the proposed models, MLP-HHO and MLP-WO, provide high accuracy in predicting diaphragm wall deflection.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Environmental Studies
Yosoon Choi, Hoang Nguyen, Xuan-Nam Bui, Trung Nguyen-Thoi
Summary: This study proposed the HHO-SVM model to predict the performance of truck-haulage systems in open-pit mines, with radial basis function identified as the best fit. Validation data demonstrated that the HHO-SVM model has high accuracy rates.
Article
Engineering, Geological
Thien Q. Huynh, Thanh T. Nguyen, Hoang Nguyen
Summary: This study examines the performance of an artificial neural network model based on a large dataset of super-large and long piles collected from 37 real projects in the Mekong Delta over the past 10 years. The results show that the random selection of training and testing datasets can significantly affect the predicted outcomes, and that displacement plays a predominant role in governing the base resistance of piles.
Article
Engineering, Civil
Xiaoguang Zhou, Hoang Nguyen, Vo Trong Hung, Chang-Woo Lee, Van-Duc Nguyen
Summary: This paper investigates the rock displacement phenomenon in order to prevent failures and collapses in tunnels and underground spaces. By analyzing historical data, a novel intelligent model called RF-DE-ANFIS was developed, which provides accurate predictions and is simpler than previous models.
Article
Energy & Fuels
Hoang Nguyen, Xuan-Nam Bui, Erkan Topal
Summary: This paper presents a method for predicting blast-induced ground vibration in open-pit mines using self-organizing neural networks (SONIA) and metaheuristic algorithms. The SONIA model was improved by employing metaheuristic algorithms including MRFO, HGS, AO, and NMRA. The study evaluated the effectiveness of the method using a case study of an open-pit coal mine in Vietnam and found that the MRFO-SONIA model provided the most reliable and accurate predictions.
INTERNATIONAL JOURNAL OF COAL GEOLOGY
(2023)
Article
Engineering, Industrial
Hoang Nguyen, Xuan-Nam Bui, Erkan Topal
Summary: This study develops three intelligent models, SpaSO-ELM, MFO-ELM, and SalSO-ELM, based on metaheuristic algorithms and ELM model, to predict the ground vibration intensity in mine blasting. These models demonstrate high reliability and accuracy in predicting peak particle velocity (PPV) and can ensure the safety of the surroundings in open-pit mines.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Environmental Sciences
Hoang Nguyen, Yosoon Choi, Masoud Monjezi, Nguyen Van Thieu, Trung-Tin Tran
Summary: This study focuses on addressing the complexity inherent in various components of blast-induced ground vibration (BIGV) and presents an enhanced nonlinear intelligent system for accurate prediction. The hybrid EO-ANFIS model emerges as the most accurate among the multiple artificial intelligence models explored.
INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT
(2023)
Proceedings Paper
Engineering, Environmental
Van-Duc Nguyen, Chang-Woo Lee, Xuan-Nam Bui, Pham Van Chung, Quang-Tuan Lai, Hoang Nguyen, Tran Thi Huong Hue, Van-Trieu Do, Ji-Whan Ahn
Summary: At COP26, more than 190 world leaders gathered to address climate change. Vietnam's Government committed to achieving net-zero carbon emissions by 2050. To achieve this goal, Vietnam needs to focus on low-carbon sustainable development technologies, with CCUS technology being a suitable option.
ADVANCES IN GEOSPATIAL TECHNOLOGY IN MINING AND EARTH SCIENCES
(2023)
Proceedings Paper
Engineering, Environmental
Xuan-Nam Bui, Chang Woo Lee, Hoang Nguyen
Summary: This paper introduces a state-of-the-art technology for modeling and controlling dust concentration from blasting operations in open-pit mines. Smart sensors mounted on an unmanned aerial vehicle were used to measure dust concentration in real-time, and meteorological conditions were taken into account. An artificial intelligence model, namely adaptive neuro-fuzzy inference system (ANFIS), was developed using the dataset to forecast PM10 concentration in the quarry. The results showed that the ANFIS model achieved a high accuracy (around 90%) and can be used to evaluate and control the air quality in the entire quarry.
ADVANCES IN GEOSPATIAL TECHNOLOGY IN MINING AND EARTH SCIENCES
(2023)
Article
Engineering, Multidisciplinary
Quang-Hieu Tran, Hoang Nguyen, Xuan-Nam Bui
Summary: This study considers and predicts blast-induced ground vibration (PPV) in open-pit mines using bagging and sibling techniques under the rigorous combination of machine learning algorithms. The results show that the bagging models provided better performance than the empirical models, with BA-ExTree being the best model with the highest accuracy (88.8%).
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Environmental Studies
Mo Yang, Ruotong Wang, Zixun Zeng, Peizhi Li
Summary: This paper proposes a hybrid forecasting model for gold prices based on the Hurst-oriented reconfiguration and machine learning approach, and validates its effectiveness by analyzing the gold prices of three major markets. The study finds negative relationships between forecasting error and the Hurst exponent, as well as between the number of embedding dimensions and the Hurst exponent. The findings provide important insights into the temporal features of the gold market and offer references for improving investment and hedging strategies.
Retraction
Environmental Studies
Xiaofeng Hu
Article
Environmental Studies
Weiwen Lin, Shan Qin, Xinzhu Zhou, Xin Guan, Yanzhao Zeng, Zeyu Wang, Yaohan Shen
Summary: The aim of this study is to explore a three-dimensional quantitative mineral prediction method that addresses the low accuracy and efficiency issues in mineral resource exploration. The experiment constructs a 3D mineral image prediction model incorporating an attention convolutional neural network (CNN). The results show that the proposed model achieves higher accuracy and precision in 3D mineral identification compared to CNN algorithms, and it demonstrates strong support for the sustainable development and strategic direction of mineral resource exploration.
Article
Environmental Studies
Liu Rong, Zhenbo Wang, Zhijun Li
Summary: The study addresses the limitation of CO2 emissions and ecological footprint in assessing pollution by introducing the load capacity factor as a metric to evaluate ecological quality. The research provides a more comprehensive evaluation of ecological quality by considering both environmental deterioration resulting from human demand and nature's ability to satisfy ecological needs.
Article
Environmental Studies
Haijiang Wu, Yu Wang
Summary: This study explores the interplay among green resources, mineral dependence, and the Urban-Rural Divide (URD) within China's pursuit of carbon neutrality. The findings indicate that rural areas have lower environmental impact but higher consumption, which affects the URD and resource utilization disparities. Carbon taxation and market trading are identified as powerful strategies for reducing emissions.
Article
Environmental Studies
Joana Duarte Ouro Alves, Weslem Rodrigues Faria
Summary: The study uses optimization methods to calculate the ideal annual rates of oil drilling and production in Brazil, and evaluates the sensitivity of these rates to various factors. The results indicate that Brazil's optimal onshore production will continue to decrease, while offshore production may be nearing its peak.
Article
Environmental Studies
Zheng Wang, Nana Feng, Wenjin Zuo, Yanhuai Jia
Summary: This study employs a Generalized Method of Moments (GMM) model to analyze the efficiency of resource markets in China from 2011 to 2020 and investigates the significant impact of resource efficiency innovations on economic growth and environmental sustainability. The findings are crucial for global sustainability endeavors and provide practical recommendations for policymakers and stakeholders.
Article
Environmental Studies
Marta G. Bekele, Judy N. Muthuri, Mengistu Bogale Ayele
Summary: This study examines the influence of national culture on Corporate Social Responsibility (CSR) in the community activities in Ethiopia's mining sector. The findings reveal that national culture variables such as religion, language, and collectivism significantly influence the CSR activities of mining companies while, power distance and masculinity have an insignificant influence on the CSR activities of the mining companies. Additionally, the qualitative data indicates that cultural values and individual characteristics also impact CSR activities.
Article
Environmental Studies
Changluan Fu, Chenyang Yu, Mengting Guo, Lin Zhang
Summary: This paper empirically analyzes the impact of ESG ratings on the financial risks of mining companies in China and explores the mechanisms involved. The findings suggest that improving ESG performance helps mitigate financial risks for mining companies.
Article
Environmental Studies
Abhibasu Sen, Karabi Dutta Choudhury
Summary: Due to its liquid nature, forecasting crude oil prices is highly stressed. In this research, the hyperparameters of LSTM and GRU were optimized using the Particle Swarm Optimization method to predict crude oil prices. A comparative study was conducted to determine which method performed better with an optimized set of hyperparameters. The results showed that GRU outperformed LSTM with a Root Mean Square Error (RMSE) of 1.23 and an R-squared value of 99.39%.
Article
Environmental Studies
Wenzhong Yue, Lijun Zhang, Tongxin Li
Summary: This paper presents a comprehensive exploration of the critical factors influencing sustainability in China's metallic resource mining sector. The study finds that carbon accounting, Information and Communication Technology (ICT) development, and Research and Development (R&D) investments have positive impacts on reducing energy expenditure. This highlights the importance of ICT development, innovation, and policy measures in advancing sustainability goals.
Article
Environmental Studies
Jingshen Zhang, Xinzhu Zhou, Rong Bai, Haoyang Dong, Tingting Tang, Zeyu Wang, Ya Yang, Feng Huang
Summary: This study investigates the impact of environmental regulatory reform on the green innovation performance of mineral enterprises and the transformation of mineral cities. Through questionnaire and data analysis, the study finds that most participants hold relatively positive views regarding environmental regulatory system reform, which has a positive impact on the green innovation performance of mineral enterprises and urban transformation.
Article
Environmental Studies
Simona Bigerna
Summary: This paper examines the relationship between energy prices, exchange rates, and inflation in the MENA region. The study utilizes a quantitative model and analyzes data from 11 countries in the region. The results show that the effects of oil price changes vary among countries and there are asymmetric contagion effects for exchange rates and inflation.
Article
Environmental Studies
Yang Liu, Yihan Huang
Summary: This study investigates the connections between fossil fuels, biomass energy, green growth, and innovation in the path to achieving carbon neutrality. Using Chinese data from 1970 to 2020 and an Autoregressive Distributed Lag (ARDL) model, the study finds a positive relationship between biofuel use and agricultural bio-energy growth in both the short and long term. It also suggests that reducing dependence on fossil fuels can enhance the cultivation of bio-energy. Therefore, the study proposes that China can transition to environmentally friendly energy sources, such as biofuels, by reducing reliance on fossil fuels like coal, in alignment with the carbon neutrality goal set by the Chinese government.
Article
Environmental Studies
Qasim Raza Syed, Farah Durani, Khalid M. Kisswani, Andrew Adewale Alola, Aaliyah Siddiqui, Ahsan Anwar
Summary: This study conducts an empirical analysis at the global level to examine the impact of natural resources and geopolitical risk on the resource curse hypothesis. The findings suggest that while natural resources promote economic growth, the interaction with geopolitical risk hinders it.